This R21 application, which responds to RFA-AG-13-003 focuses on multimorbidity in heart failure (HF). The incidence of HF did not change appreciably in the past 2 decades while survival improved leading to a highly burdensome epidemic of hospitalizations among older individuals. Care providers and systems are ill-equipped to care for such patients because clinical guidelines are disease-centric, whereas patients with HF present with multimorbidity. The failure to adequately understand multimorbidity in HF likely explains why disease management strategies in HF are only partially effective and why the epidemic of hospitalizations in HF is not contained. Finally, patients with HF are increasingly referred to post acute care (PAC), yet the association between multimorbidity, PAC use and outcome after PAC is poorly characterized. This gap in knowledge can be addressed by secondary analyses of longitudinal datasets that capture the entire spectrum of care including PAC as proposed herein. The central tenet of our application is that the failure to control the epidemic of HF reflects an inadequate understanding of multimorbidity in HF, which has never been examined in the community and is inadequately managed by current disease-centric strategies. For novel approaches to be effective, we must first address in clinically relevant community practices, how comorbid conditions present and cluster at the time of diagnosis and vary by the type of HF (preserved vs. reduced EF), how multimorbidity influences outcomes (hospitalizations, PAC use and death) and specifically what combination of comorbid conditions are associated with the worse outcomes. We will execute the following aims: in Aim 1, we will examine the distribution and clustering of comorbid conditions in a community cohort of persons with incident (first diagnosis) of HF. We will study how the distribution of comorbidities differs by type of HF (preserved vs. reduced EF). In Aim 2, we will assess how multimorbidity impact outcome (hospitalizations, PAC use and death), by linking the data from our community HF cohort to the State of Minnesota nursing home files. Linking rich clinical data to administrative data on PAC use will create a uniquely comprehensive dataset to assess the presentation and trajectory of persons with HF across care delivery settings, including hospital and PAC. Capturing the full health care experience of these patients is indispensable to understand multimorbidity in HF and to identify combinations of conditions that contribute to exceptionally poor outcomes. These secondary analyses will provide important information to target specific combinations of conditions to evaluate new management strategies in HF. The proposed research is distinctly feasible as it capitalizes on the infrastructure of the Rochester Epidemiology Project (R01 AG034676) and builds on the research team's robust experience.